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Many real networks are directed.
However, many real networks have more complex overlapping community structures.
Many real networks have been reported to be scale-free [2].
However, time delays, including coupling delay and node delay, usually exist in many real networks.
Many real networks, including those in social, technological, and biological realms, are small-world networks.
This assumption cannot be used in many real networks with evolving or adaptive couplings, e.g., flocks of robots [18].
Similar(36)
We note that the DREAM networks, like many real biological networks, contain feedback loops that cannot be modeled by methods based on causal Bayesian networks such as MCMC-Mallows and IDA.
Watts/Strogatz introduced a class of networks that combined the high clustering coefficient observed in many real world networks (and in lattices) with the logarithmically growing mean distance also observed in some real world networks (and in Erdosz-Renyi graphs).
However, none of these studies deals either with true social network substrates or with more specific mesoscopic structures, in particular, the community structure present in many real social networks.
In many real complex networks, the clustering coefficient tends to be a non-zero number when the size of the network grows, while in random networks, it tends to be zero.
Furthermore, many real complex networks cannot synchronize themselves or synchronize with the desired orbits.
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many real life networks
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many real people
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many environmental networks
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many overseas networks
many biomolecular networks
many corporate networks
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